Secreted and membrane tethered matrix metalloproteinases (MMPs) are key homeostatic proteases regulating the extracellular signaling and structural matrix environment of cells and tissues. For drug targeting of proteases, selectivity for individual molecules is highly desired and can be met by high yield active site specificity profiling. Using the high throughput Proteomic Identification of protease Cleavage Sites (PICS) method to simultaneously profile both the prime and non-prime sides of the cleavage sites of nine human MMPs, we identified more than 4300 cleavages from P6 to P6' in biologically diverse human peptide libraries. MMP specificity and kinetic efficiency were mainly guided by aliphatic and aromatic residues in P1' (with a ~32-93% preference for leucine depending on the MMP), and basic and small residues in P2' and P3', respectively. A wide differential preference for the hallmark P3 proline was found between MMPs ranging from 15 to 46%, yet when combined in the same peptide with the universally preferred P1' leucine, an unexpected negative cooperativity emerged. This was not observed in previous studies, probably due to the paucity of approaches that profile both the prime and non-prime sides together, and the masking of subsite cooperativity effects by global heat maps and iceLogos. These caveats make it critical to check for these biologically highly important effects by fixing all 20 amino acids one-by-one in the respective subsites and thorough assessing of the inferred specificity logo changes. Indeed an analysis of bona fide MEROPS physiological substrate cleavage data revealed that of the 37 natural substrates with either a P3-Pro or a P1'-Leu only 5 shared both features, confirming the PICS data. Upon probing with several new quenched-fluorescent peptides, rationally designed on our specificity data, the negative cooperativity was explained by reduced non-prime side flexibility constraining accommodation of the rigidifying P3 proline with leucine locked in S1'. Similar negative cooperativity between P3 proline and the novel preference for asparagine in P1 cements our conclusion that non-prime side flexibility greatly impacts MMP binding affinity and cleavage efficiency. Thus, unexpected sequence cooperativity consequences were revealed by PICS that uniquely encompasses both the non-prime and prime sides flanking the proteomic-pinpointed scissile bond.

Post-translational modifications enable extra layers of control of the proteome, and perhaps the most important is proteolysis, a major irreversible modification affecting every protein. The intersection of the protease web with a proteome sculpts that proteome, dynamically modifying its state and function. Protease expression is distorted in cancer, so perturbing signaling pathways and the secretome of the tumor and reactive stromal cells. Indeed many cancer biomarkers are stable proteolytic fragments. It is crucial to determine which proteases contribute to the pathology versus their roles in homeostasis and in mitigating cancer. Thus the full substrate repertoire of a protease, termed the substrate degradome, must be deciphered to define protease function and to identify drug targets. Degradomics has been used to identify many substrates of matrix metalloproteinases that are important proteases in cancer. Here we review recent degradomics technologies that allow for the broadly applicable identification and quantification of proteases (the protease degradome) and their activity state, substrates, and interactors. Quantitative proteomics using stable isotope labeling, such as ICAT, isobaric tags for relative and absolute quantification (iTRAQ), and stable isotope labeling by amino acids in cell culture (SILAC), can reveal protease substrates by taking advantage of the natural compartmentalization of membrane proteins that are shed into the extracellular space. Identifying the actual cleavage sites in a complex proteome relies on positional proteomics and utilizes selection strategies to enrich for protease-generated neo-N termini of proteins. In so doing, important functional information is generated. Finally protease substrates and interactors can be identified by interactomics based on affinity purification of protease complexes using exosite scanning and inactive catalytic domain capture strategies followed by mass spectrometry analysis. At the global level, the N terminome analysis of whole communities of proteases in tissues and organs in vivo provides a full scale understanding of the protease web and the web-sculpted proteome, so defining metadegradomics.